Uterine Artery Doppler Ultrasound for Predicting Preeclampsia During Pregnancy: A Meta-analysis

doi:10.21203/rs.3.rs-3127346/v1

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Uterine Artery Doppler Ultrasound for Predicting Preeclampsia During Pregnancy: A Meta-analysis

https://doi.org/10.21203/rs.3.rs-3127346/v1

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Background

Accurate prediction of preeclampsia can improve maternal outcomes. However, the utility of uterine artery Doppler imaging in the prediction of preeclampsia remains unclear. To investigate the accuracy of uterine artery Doppler ultrasound parameters in predicting preeclampsia during pregnancy.

Methods

We searched databases for studies using uterine artery Doppler imaging to predict preeclampsia from inception to March 23, 2023. The main outcome was preeclampsia. We assessed study bias using QUADAS-2.

Results

Of 40 studies, 19 used the pulsatility index (PI) to predict preeclampsia, with sensitivity 0.05 (95% CI 0.02–0.08) and specificity 0.44 (95% CI 0.28–0.61). Nine studies used the resistance index (RI), with sensitivity 0.13 (95% CI 0.05–0.27) and specificity 0.31 (95% CI 0.07–0.63). Three studies used the systolic/diastolic (S/D) ratio, with sensitivity 0.50 (95% CI 0.30–0.67) and specificity 0.86 (95% CI 0.68–0.95). Nine studies used notching, with sensitivity 0.20 (95% CI 0.09–0.35) and specificity 0.60 (95% CI 0.23–0.90).

Conclusions

Uterine artery Doppler parameters predicted preeclampsia differently. PI and RI had low sensitivity and specificity. S/D ratio had high sensitivity and specificity, useful for predicting preeclampsia. Notching had low sensitivity and high specificity. Uterine artery Doppler alone has limited use in predicting preeclampsia.

preeclampsia

doppler

uterine artery

meta-analysis

Preeclampsia is a multisystem disorder of women characterized by the development of hypertension and proteinuria after the 20th week of gestation [1]. This disorder causes profound complications during pregnancy, including pulmonary edema, acute renal failure, and coagulopathy [2]. Preeclampsia is one of the foremost causes of maternal morbidity and mortality worldwide and has detrimental effects on the fetus [3]. Furthermore, long-term health disorders, such as cardiovascular disease, can develop in women with preeclampsia [4]. The incidence of preeclampsia varies between 3% and 5% across different racial and environmental contexts and according to different diagnostic criteria [5–7].

Preeclampsia is caused by multiple mechanisms, among which inadequate placental implantation is believed to play a significant role. Insufficient invasion by trophoblasts into the deeper maternal myometrial arterioles results in aberrant remodeling of spiral arteries [8, 9]. These defective spiral arteries exhibit greater resistance and less oxygenation than their normal counterparts, resulting in placental ischemia, hypoxia, and necrosis. The necrotic trophoblasts release antiangiogenic factors and proinflammatory cytokines into the maternal circulation, which trigger a systemic response in endothelial cells. These cascading events contribute to the clinical manifestations of preeclampsia, which typically appear several weeks after the initial insult [10, 11].

According to the American College of Obstetricians and Gynecologists, a patient’s medical history should guide the screening for preeclampsia [12]. However, this guidance results in the detection of preeclampsia in only approximately 30% of cases [13]. To enhance the accuracy and efficacy of screening methods, numerous studies have been conducted to establish predictive tests for preeclampsia. Doppler velocimetry, which is used to evaluate uterine arteries (UtAs), is a validated noninvasive method of assessing placental perfusion [14]. Abnormal results of UtA velocimetry indicate incomplete remodeling of spiral arteries [15]; thus, this method shows promise in detecting preeclampsia. This study aimed to investigate the accuracy of uterine artery Doppler ultrasound in predicting preeclampsia during pregnancy.

This study is a meta-analysis which contains no participants and ethics approval and consent to participate is not applicable.

Search strategy

We searched PubMed, Embase, the Cochrane Library, and Web of Science for randomized clinical trials and observational studies, conducted from database creation to March 23, 2023, in which uterine artery Doppler imaging was used to predict preeclampsia. The terms “preeclampsia,” “pregnancy,” “uterine artery Doppler,” “sensitivity,” “specificity,” and “prediction” were searched individually or in combination. Only studies of humans published in English were included in the search, and the search strategy is detailed in the Additional file 1.

Inclusion and exclusion criteria

To be included, studies had to (1) focus on pregnant women, (2) involve the use of uterine artery Doppler ultrasonography, and (3) be published in English. We excluded (1) abstracts, letters, talks, and reviews; (2) studies in which uterine artery Doppler ultrasonography was not used; and (3) duplicate studies with data already included in the meta-analysis.

Data extraction

Two reviewers independently analyzed all included studies and extracted the following data: names of authors; year of publication; type of study; Doppler ultrasound parameters; geographical region; type of data set; sample size of experimental and control groups; and sensitivity and specificity data.

Quality assessment

Two reviewers independently scored the quality of the included studies using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) criteria [16]. In the QUADAS-2, whose maximum score is 7, each study was scored according to whether they met seven criteria: “yes” (score of 1) and “unclear” or “no” (score of 0).

Statistical methods

The data were analyzed using R and RStudio software version 4.3.0. Diagnostic effectiveness of different uterine artery Doppler parameters in predicting preeclampsia was measured using sensitivity, specificity, and summary receiver operating characteristic (SROC) curves. A crosshair plot was generated by displaying the posterior means for each study as the summary points, along with paired lines showing the corresponding 95% confidence intervals (CIs) for sensitivity and false-positive rate (1-specificity) [17]. The resulting posterior density plot depicted the relative importance of the two studied metrics. The SROC was also based on a combination of sensitivity and specificity. The risk of bias was assessed using the Robvis and metafor packages in RStudio [18]. The sensitivity and specificity of the summaries were measured using the meta4diag package in RStudio. Publication bias was detected using Deeks’ funnel plot asymmetry test [19].

Basic characteristics of the included studies

We found 2471 found potentially eligible studies after a thorough literature search. After duplicates were excluded and titles and abstracts were checked, 114 studies remained; after reading the full text, we determined that 40 studies met the inclusion requirements and were used in the analysis (Fig. 1).

The main characteristics and QUADAS-2 scores of the included studies are listed in Table 1. In total, the 40 studies involved 1232 patients with preeclampsia and 18,718 healthy pregnant women (controls). Preeclampsia was diagnosed during pregnancy via uterine artery Doppler ultrasound. All studies were mostly conducted in Asian populations and published between 2001 and 2022. In all studies, in-hospital records were used as the datasets. Most studies were prospective; only three were retrospective. Most studies were of good quality, and 24 studies were of high quality (QUADAS-2 scores of ≥ 6). The results of the quality assessment are illustrated in Fig. 2A and B.

Table 1

Main characteristics of 40 studies included in meta-analysis
Study	Study design	Region	Dataset type	Parameters	N, Test	N, Control	QUADAS
Soongsatitanon 2022	Prospective	Thailand	Hospital	PI	29	324	6
Prakansamut 2019	Prospective	Thailand	Hospital	PI	35	370	6
Wairachpanich 2022	Prospective	Thailand	Hospital	PI	25	368	6
Tianthong 2021	Prospective	Thailand	Hospital	PI	31	354	3
Okwudire 2019	Prospective	Nigeria	Hospital	PI	13	157	3
Okwudire 2019	Prospective	Nigeria	Hospital	RI	13	157	3
Okwudire 2019	Prospective	Nigeria	Hospital	S/D	13	157	3
Okwudire 2019	Prospective	Nigeria	Hospital	Notching	13	157	3
Aksornphusitaphong 2018	Prospective	Thailand	Hospital	PI	18	309	6
Puttapitakpong 2016	Prospective	Thailand	Hospital	PI	25	375	3
Puttapitakpong 2016	Prospective	Thailand	Hospital	Notching	25	375	3
Maged 2017	Prospective	Egypt	Hospital	RI	45	297	6
Trongpisutsak 2021	Prospective	Thailand	Hospital	PI	22	421	6
Trongpisutsak 2021	Prospective	Thailand	Hospital	Notching	22	421	6
Adefisan 2020	Prospective	Nigeria	Hospital	RI	10	70	7
Adefisan 2020	Prospective	Nigeria	Hospital	PI	10	70	7
Melchiorre 2008	Prospective	UK	Hospital	RI	90	2968	6
Melchiorre 2008	Prospective	UK	Hospital	Notching	90	2968	6
Fouad 2016	Prospective	Egypt	Hospital	RI	71	701	6
Fouad 2016	Prospective	Egypt	Hospital	PI	71	701	6
Martin 2001	prospective	UK	Hospital	PI	63	3045	6
Jamal 2013	Prospective	Iran	Hospital	PI	23	412	6
Prajapati 2013	Prospective	India	Hospital	PI	33	167	3
Fratelli 2008	Retrospective	Italy	Hospital	RI	5	71	5
Bhattacharyya 2012	Prospective	India	Hospital	RI	7	120	6
Shahid 2021	Retrospective	Pakistan	Hospital	RI	40	35	7
Shahid 2021	Retrospective	Pakistan	Hospital	Notching	40	35	7
Shahid 2021	Retrospective	Pakistan	Hospital	Notching	40	35	7
Khanam 2021	Prospective	India	Hospital	PI	9	91	6
Stoenescu 2021	Prospective	Romania	Hospital	S/D	33	26	2
Stoenescu 2021	Prospective	Romania	Hospital	PI	33	26	2
Stoenescu 2021	Prospective	Romania	Hospital	Notching	24	111	2
Das 2022	Prospective	India	Hospital	PI	18	124	6
Nagar 2015	Prospective	India	Hospital	S/D	20	480	3
Nagar 2015	Prospective	India	Hospital	RI	20	480	3
Nagar 2015	Prospective	India	Hospital	Notching	20	480	3
Verma 2016	Prospective	India	Hospital	PI	13	152	6
Choorakuttil 2022	Prospective	India	Hospital	PI	72	396	3
Springer 2020	Prospective	Austria	Hospital	PI	24	356	7
Springer 2020	Prospective	Austria	Hospital	Notching	24	356	7
PI, pulsatility index; RI, resistance index; S/D, systolic/diastolic ratio.

Efficacy of pulsatility index in predicting preeclampsia

The pulsatility index (PI) was reported in 19 studies. For predicting preeclampsia. The PI had a sensitivity of 0.05 (95% CI 0.02–0.08) and specificity of 0.44 (95% CI 0.28–0.61; Fig. 3). The crosshair and posterior density plots of PI are shown in Additional file 2.

Efficacy of resistance index in predicting preeclampsia

The resistance index (RI) was reported in nine studies. For predicting preeclampsia, the RI had a sensitivity of 0.13 (95% CI 0.05–0.27) and specificity of 0.31 (95% CI 0.07–0.63; Fig. 4). The crosshair and posterior density plots of RI are shown in Additional file 3.

Efficacy of systolic/diastolic ratio in predicting preeclampsia

The systolic/diastolic (S/D) ratio was reported in three studies. For predicting preeclampsia, the S/D ratio had a sensitivity of 0.50 (95% CI 0.30–0.67) and specificity of 0.86 (95% CI 0.68–0.95; Fig. 5). The crosshair and posterior density plots of S/D are shown in Additional file 4.

Efficacy of notching in predicting preeclampsia

Notching was reported in nine studies. Notching had a sensitivity of 0.20 (95% CI 0.09–0.35) and specificity of 0.60 (95% CI 0.23–0.90; Fig. 6) in predicting preeclampsia. The crosshair and posterior density plots of PI are shown in Additional file 5.

Publication bias

For the result of the asymmetry test, P < 0.01, which indicated that the publication bias was significant (Additional file 6).

In this study, different parameters of uterine artery Doppler ultrasound predicted preeclampsia differently. In particular, the sensitivity and specificity were low when the parameters PI and RI were used alone, whereas they were high when S/D was used. Uterine artery Doppler ultrasound is an important method for evaluating high-risk pregnancies with preeclampsia during early pregnancy. Many studies have explored the utility of Doppler indicators in predicting preeclampsia, but the results are controversial. Uterine arterial blood flow and RI are commonly used predictors of preeclampsia. A meta-analysis indicated that uterine artery RI and PI predicted preeclampsia more accurately than blood flow [20]. However, other studies have shown that an RI of ≥ 0.58 and a blood flow rate of > 105 mL/min were more accurate predictors at approximately 20 weeks of gestation [21, 22], but these findings might vary depending on the research object and technique used.

The superiority of the Doppler index of the right uterine artery over that of the left in predicting preeclampsia is controversial. One study showed that an RI of ≥ 0.61 and a blood flow rate of > 123 mL/min for the right uterine artery were independent predictors of preeclampsia [23]. However, another study demonstrated that the predictive abilities of left and right uterine artery indices are equivalent [24], which may be attributable to differences in individual arterial structure and blood flow. The position of the placenta also affects Doppler prediction ability. Investigators have reported that hemodynamic changes in the posterior placenta were more pronounced than those of other placental locations and that the predictive power of the PI and RI was higher [22]. Other studies have shown that placental position does not affect the predictive value of the Doppler index [25].

Uterine artery Doppler ultrasound can be used for predicting preeclampsia during pregnancy; however, its predictive ability is constrained by various factors, resulting in differences variable outcomes. To improve prediction accuracy, both sensitivity and specificity need to be considered, but only one predictive indicator, specificity, is most often selected. Excessively high false-positive results lead to excessive intervention, increase maternal anxiety, and even affect the quality of life of pregnant women. Reducing the cutoff value of the Doppler index can improve sensitivity but not specificity, leading to more false-positive results. One meta-analysis showed that a RI of ≥ 0.58 has only 67% specificity, whereas the specificity of a RI of ≥ 0.65 can reach 89% [26]. Other studies have confirmed that the sensitivity of a RI of ≥ 0.58 is as high as 97%, but the specificity is only 63%. When the RI was ≥ 0.65, the sensitivity decreased to 82%, but the specificity increased to 81% [24]. This indicates that under the same conditions, higher RI cutoff values can achieve higher specificity.

Many investigators use receiver operating characteristic curve analysis and choose Doppler parameters with higher specificity as predictive indicators. Studies have shown that when specificity reaches 85%, RI ≥ 0.63 and PI ≥ 1.45, and an RI of ≥ 0.66 in the posterior placenta is a predictor of preeclampsia [23]. Another study demonstrated that 90% specificity is achieved by an RI of ≥ 0.715 and a PI of ≥ 2.145 in the UtAs [27]. This further confirms that a higher Doppler index cutoff value can help achieve higher specificity. Other investigators have used different methods to improve the specificity of Doppler examination. For example, using a bilateral uterine arterial RI of ≥ 0.63 and PI of ≥ 1.45, Velauthar et al. achieved 89% specificity [28]. Alternatively, to establish a predictive model with high specificity, logistic regression analysis can be performed with a combination of risk factors and Doppler indicators to identify variables with high specificity.

Of the 40 included studies, 9 had populations from India and 9 from Thailand; thus, the findings may not be globally representative. Also, the meta4diag program package in R software, which was used for the analysis, did not include a heterogeneity test. Therefore, additional studies with more convincing results may be needed to verify the utility of Doppler parameters in predicting preeclampsia.

Our meta-analysis of 40 studies showed that different uterine artery Doppler ultrasound parameters predicted preeclampsia differently. In particular, the sensitivity and specificity were low when PI and RI were used, and the utility of uterine Doppler artery alone in predicting preeclampsia was limited. When S/D was used, the sensitivity and specificity were high, suggesting that S/D can be used as a selective indicator for predicting preeclampsia. The use of notching to predict preeclampsia had a low sensitivity and a high specificity. Because of regional differences in research and the tendency to prioritize specificity as a predictor of preeclampsia, the overall accuracy of prediction may be limited.

Cis = confidence intervals

PI = pulsatility index

RI = resistance index

S/D = systolic/diastolic

SROC = summary receiver operating characteristic

UtAs = uterine arteries

Ethics approval and consent to participate

This study is a meta-analysis which contains no participants and ethics approval and consent to participate is not applicable.

Consent for publication

Not applicable.

Availability of data and materials

All data generated or analysed during this study are included in this published article and its supplementary information files.

Competing interests

The authors declare that they have no competing interests.

Funding

The study was supported by Shanghai Changning District Science and Technology Committee [grant number CNKW2022Y33]; The Innovative talent base for master and doctor of hypertensive disorder complicating pregnancy [grant number RCJD2022S06].

Author Contributions

LC contributed to study design. BH contributed to drafting of the manuscript. YZ and TC contributed to data collection. YG and BY contributed to statistical analysis. All authors have read and approved the final manuscript.

Acknowledgements

Not applicable.

Chappell LC, Cluver CA, Kingdom J, Tong S. Pre-eclampsia. Lancet. 2021;398:341-54.
Phipps EA, Thadhani R, Benzing T, Karumanchi SA. Pre-eclampsia: pathogenesis, novel diagnostics and therapies. Nat Rev Nephrol. 2019;15:275-89.
Khan KS, Wojdyla D, Say L, Gülmezoglu AM, Van Look PF. WHO analysis of causes of maternal death: a systematic review. Lancet. 2006;367:1066-74.
Bellamy L, Casas JP, Hingorani AD, Williams DJ. Pre-eclampsia and risk of cardiovascular disease and cancer in later life: systematic review and meta-analysis. Bmj. 2007;335:974.
Abalos E, Cuesta C, Grosso AL, Chou D, Say L. Global and regional estimates of preeclampsia and eclampsia: a systematic review. Eur J Obstet Gynecol Reprod Biol. 2013;170:1-7.
Say L, Chou D, Gemmill A, Tunçalp Ö, Moller AB, Daniels J, et al. Global causes of maternal death: a WHO systematic analysis. Lancet Glob Health. 2014;2:e323-33.
Ananth CV, Keyes KM, Wapner RJ. Pre-eclampsia rates in the United States, 1980-2010: age-period-cohort analysis. Bmj. 2013;347:f6564.
Burton GJ, Redman CW, Roberts JM, Moffett A. Pre-eclampsia: pathophysiology and clinical implications. Bmj. 2019;366:l2381.
Redman CW, Sargent IL, Staff AC. IFPA Senior Award Lecture: making sense of pre-eclampsia - two placental causes of preeclampsia? Placenta. 2014;35 Suppl:S20-5.
Sharma S, Norris WE, Kalkunte S. Beyond the threshold: an etiological bridge between hypoxia and immunity in preeclampsia. J Reprod Immunol. 2010;85:112-6.
Fukui A, Yokota M, Funamizu A, Nakamua R, Fukuhara R, Yamada K, et al. Changes of NK cells in preeclampsia. Am J Reprod Immunol. 2012;67:278-86.
Committee Opinion No. 638: First-Trimester Risk Assessment for Early-Onset Preeclampsia. Obstetrics & Gynecology. 2015;126:e25-e7.
Onwudiwe N, Yu CK, Poon LC, Spiliopoulos I, Nicolaides KH. Prediction of pre-eclampsia by a combination of maternal history, uterine artery Doppler and mean arterial pressure. Ultrasound Obstet Gynecol. 2008;32:877-83.
Campbell S, Diaz-Recasens J, Griffin DR, Cohen-Overbeek TE, Pearce JM, Willson K, et al. New doppler technique for assessing uteroplacental blood flow. Lancet. 1983;1:675-7.
Prefumo F, Campbell S, Jauniaux E. Maternal blood flow to the placenta. Bjog. 2019;126:972.
Whiting Penny F, Rutjes Anne W, Westwood Marie E, Mallett Susan DJJ, Reitsma Johannes B, Lee ang Mariska M, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Annals of internal medicine. 2011;155:529.
Phillips B, Stewart LA, Sutton AJ. ‘Cross hairs’ plots for diagnostic meta‐analysis. Research Synthesis Methods. 2010;1:308-15.
McGuinness L, Higgins J: Risk-of-bias VISualization (robvis): An R package and Shiny web app for visualizing risk-of-bias assessments. Res Synth Methods. 2021; 12 (1): 55-61. In.
Deeks JJ, Macaskill P, Irwig L. The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. Journal of clinical epidemiology. 2005;58:882-93.
Yu C, Papageorghiou A, Parra M, Palma Dias R, Nicolaides K, Group FMFSTS. Randomized controlled trial using low‐dose aspirin in the prevention of pre‐eclampsia in women with abnormal uterine artery Doppler at 23 weeks' gestation. Ultrasound in obstetrics & gynecology. 2003;22:233-9.
Fleischer A, Schulman H, Farmakides G, Bracero L, Grunfeld L, Rochelson B, et al. Uterine artery Doppler velocimetry in pregnant women with hypertension. American journal of obstetrics and gynecology. 1986;154:806-12.
North R, Ferrier C, Long Da, Townend K, Kincaid-Smith P. Uterine artery Doppler flow velocity waveforms in the second trimester for the prediction of preeclampsia and fetal growth retardation. Obstetrics & Gynecology. 1994;83:378-86.
Gómez O, Figueras F, Fernández S, Bennasar M, Martínez J, Puerto B, et al. Reference ranges for uterine artery mean pulsatility index at 11–41 weeks of gestation. Ultrasound in Obstetrics and Gynecology: The Official Journal of the International Society of Ultrasound in Obstetrics and Gynecology. 2008;32:128-32.
Christina K, Smith GC, Papageorghiou AT, Cacho AM, Nicolaides KH, Group FMFSTS. An integrated model for the prediction of preeclampsia using maternal factors and uterine artery Doppler velocimetry in unselected low-risk women. American journal of obstetrics and gynecology. 2005;193:429-36.
Ventura W, De Paco Matallana C, Prieto‐Sanchez MT, Macizo MI, Pertegal M, Nieto A, et al. Uterine and umbilical artery Doppler at 28 weeks for predicting adverse pregnancy outcomes in women with abnormal uterine artery Doppler findings in the early second trimester. Prenatal Diagnosis. 2015;35:294-8.
Cnossen JS, Morris RK, Ter Riet G, Mol BW, Van Der Post JA, Coomarasamy A, et al. Use of uterine artery Doppler ultrasonography to predict pre-eclampsia and intrauterine growth restriction: a systematic review and bivariable meta-analysis. Cmaj. 2008;178:701-11.
Yu C, Khouri O, Onwudiwe N, Spiliopoulos Y, Nicolaides K. Prediction of pre‐eclampsia by uterine artery Doppler imaging: relationship to gestational age at delivery and small‐for‐gestational age. Ultrasound in Obstetrics and Gynecology: The Official Journal of the International Society of Ultrasound in Obstetrics and Gynecology. 2008;31:310-3.
Velauthar L, Plana M, Kalidindi M, Zamora J, Thilaganathan B, Illanes S, et al. First‐trimester uterine artery Doppler and adverse pregnancy outcome: a meta‐analysis involving 55 974 women. Ultrasound in Obstetrics & Gynecology. 2014;43:500-7.

No competing interests reported.

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Version 1

posted

You are reading this latest preprint version

Uterine Artery Doppler Ultrasound for Predicting Preeclampsia During Pregnancy: A Meta-analysis

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Search strategy

Inclusion and exclusion criteria

Data extraction

Quality assessment

Statistical methods

Results

Basic characteristics of the included studies

Efficacy of pulsatility index in predicting preeclampsia

Efficacy of resistance index in predicting preeclampsia

Efficacy of systolic/diastolic ratio in predicting preeclampsia

Efficacy of notching in predicting preeclampsia

Publication bias

Discussion

Conclusions

Abbreviations

Declarations

Ethics approval and consent to participate

Consent for publication

Availability of data and materials

Competing interests

Funding

Author Contributions

Acknowledgements

References

Additional Declarations

Supplementary Files

Status:

Version 1